Method and System for Navigating Vehicles Based on Road Conditions Determined in Real-Time

2. The method of claim 1, further comprising capturing the first dataset and the second dataset using at least one of a plurality of sensors attached to the vehicle, wherein the plurality of sensors comprises at least one of a camera, a Kinect like sensor, a distance sensor, or an Infrared (IR) sensor.

3. The method of claim 1, wherein detecting the vanishing point comprises extending at least two of the plurality of edges till an intersection point of the at least two of the plurality of edges is identified.

4. The method of claim 1, further comprising generating a topographic map for the road based on the value assigned to each of the plurality of grids, wherein the topographic map represents the road conditions.

5. The method of claim 1, further comprising determining a relationship between the first dataset and the second dataset by mapping Two Dimensional (2D) points in a 2D image with Three dimensional (3D) points in the real-world.

6. The method of claim 1, further comprising navigating the vehicle based on the digital elevation image comprising the plurality of grids having values assigned from the predefined value range.

7. The method of claim 1, further comprising determining a plurality of vehicle attributes associated with the vehicle, wherein the plurality of vehicle attributes comprises wheel width of the vehicle, ground clearance height of the vehicle, a center of gravity (CG) of the vehicle, wheel base of the vehicle, and number of wheels of the vehicle.

8. The method of claim 7, further comprising identifying a potential path from a plurality of paths for navigating the vehicle on the road based on the value assigned to each of the plurality of grids in the digital elevation image and the plurality of vehicle attributes associated with the vehicle.

9. The method of claim 8, further comprising determining a confidence score associated with the potential path based on a condition of the potential path and a vehicle action while navigating the potential path.

10. The method of claim 9, further comprising generating at least one warning when the confidence score associated with the potential path is less than a predefined threshold value.

12. The system of claim 11, wherein the processor instructions further cause the processor to capture the first dataset and the second dataset using at least one of a plurality of sensors attached to the vehicle, wherein the plurality of sensors comprises at least one of a camera, a Kinect like sensor, a distance sensor, or an Infrared (IR) sensor.

13. The system of claim 11, wherein the processor instructions further cause the processor to detect the vanishing point by extending at least two of the plurality of edges till an intersection point of the at least two of the plurality of edges is identified.

14. The system of claim 11, wherein the processor instructions further cause the processor to generate a topographic map for the road based on the value assigned to each of the plurality of grids, wherein the topographic map represents the road conditions.

15. The system of claim 11, wherein the processor instructions further cause the processor to determine a relationship between the first dataset and the second dataset by mapping Two Dimensional (2D) points in a 2D image with Three dimensional (3D) points in the real-world.

16. The system of claim 11, wherein the processor instructions further cause the processor to navigate the vehicle based on the digital elevation image comprising the plurality of grids having values assigned from the predefined value range.

17. The system of claim 11, wherein the processor instructions further cause the processor to determine a plurality of vehicle attributes associated with the vehicle, wherein the plurality of vehicle attributes comprises wheel width of the vehicle, ground clearance height of the vehicle, a center of gravity (CG) of the vehicle, wheel base of the vehicle, and number of wheels of the vehicle.

18. The system of claim 17, wherein the processor instructions further cause the processor to identify a potential path from a plurality of paths for navigating the vehicle on the road based on the value assigned to each of the plurality of grids in the digital elevation image and the plurality of vehicle attributes associated with the vehicle.